Fundamentals of Data Analytics

Estratto della scheda di revisione

Course Outline

  1. Types of Analytics
  2. Data Collection and Storage
  3. Descriptive Statistics
  4. Predictive Analytics
  5. Prescriptive Analytics
  6. Measures of Central Tendency
  7. Measures of Spread
  8. Sampling Methods
  9. Types of Data
  10. Data Measurement Scales
  11. Dispersion Measures
  12. Outliers and Influence

1. Types of Analytics

Key Concepts & Definitions

  • Descriptive analytics: The process of analyzing data that has already occurred to summarize and understand past events, providing insights into what has happened. It involves techniques like calculating averages, medians, modes, and measures of spread (variance, standard deviation).
  • Predictive analytics: The use of mathematical and statistical models to analyze past data in order to predict or classify future events. It involves building models that can forecast outcomes based on historical patterns, applicable to both numerical and categorical predictions.
  • Prescriptive analytics: The process of using data assets as a guide to influence or change future outcomes. It involves creating data-driven solutions to control or optimize events, guiding decision-making to achieve desired results.

Essential Points

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Anteprima del quiz

1. What is predictive analytics?

2. What is the primary purpose of the data collection and storage process in data analytics?

3. What is the primary role of descriptive statistics?

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Anteprima delle flashcard

Types of Analytics — roles?

Descriptive, predictive, prescriptive; analyze past, forecast, guide actions.

Data collection — purpose?

Gather and organize data for analysis and insights.

Population parameters — what?

True values describing entire population.

Sample statistics — purpose?

Estimate population parameters from samples.

Descriptive statistics — focus?

Summarize data using mean, median, mode.

Mean — definition?

Average of data points.

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Domande frequenti

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